Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add duonginspace/claude-code-databricks-ml --skill explain-codegit clone --depth 1 https://github.com/duonginspace/claude-code-databricks-mlWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/duonginspace/claude-code-databricks-ml/explain-code)<a href="https://agentmods.dev/skills/duonginspace/claude-code-databricks-ml/explain-code"><img src="https://agentmods.dev/badge/skills/duonginspace/claude-code-databricks-ml/explain-code/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/duonginspace/claude-code-databricks-ml/explain-code"><img src="https://agentmods.dev/badge/skills/duonginspace/claude-code-databricks-ml/explain-code.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.00138 |
| Opus 5.5 | $0.00015 | $0.00055 |
| Sonnet 5.5 | $0.00008 | $0.00028 |
| Haiku 4.5 | $0.00004 | $0.00014 |
Grade A, and why
explain-code scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to explain-code — 25 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
When explaining code, always include:
- Start with an analogy: Compare the code to something from everyday life
- Draw a diagram: Use ASCII art to show the flow, structure, or relationships
- Walk through the code: Explain step-by-step what happens
- Highlight a gotcha: What's a common mistake or misconception?
Keep explanations conversational. For complex concepts, use multiple analogies.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 13 lines · 38 tokens per session scan A 30fba40a728c
explain-code is a skill published in the GitHub repository duonginspace/claude-code-databricks-ml (5 stars, last pushed 6mo ago), licensed MIT. It adds 38 tokens to every session and 138 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to explain-code, differing in 25 lines, and is treated as a copy.
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